docs: def set_dtreat_interp_indch(self, indch=None):
          """ Set the indices of the channels for which to interpolate data
  
          The index can be provided as:
              - A 1d np.ndarray of boolean or int indices of channels
                  => interpolate data at these channels for all times
              - A dict with:
                  * keys = int indices of times
                  * values = array of int indices of chan. for which to interpolate
  
          Time indices refer to self.ddataRef['t']
          Channel indices refer to self.ddataRef['X']
          """
          lC = [indch is None, type(indch) in [np.ndarray,list], type(indch) is dict]
          assert any(lC)
          if lC[2]:
              lc = [type(k) is int and k<self._ddataRef['nt'] for k in indch.keys()]
              assert all(lc)
              for k in indch.keys():
                  assert hasattr(indch[k],'__iter__')
                  indch[k] = _format_ind(indch[k], n=self._ddataRef['nch'])
          elif lC[1]:
              indch = np.asarray(indch)
              assert indch.ndim==1
              indch = _format_ind(indch, n=self._ddataRef['nch'])
          self._dtreat['interp-indch'] = indch
          self._ddata['uptodate'] = False